from tensorflow.keras import layers, models, Input

# Define input layer explicitly
input_layer = Input(shape=(2,))  # Explicit input layer


# Instantiate the model.
linear_1d_model = tf.keras.Sequential()

linear_1d_model.add(input_layer)

# Add the normalization layer.
linear_1d_model.add(hp_normalizer)

# Add the single neuron.
linear_1d_model.add(Dense(1, input_shape=(1,)))

# Display the model summary.
linear_1d_model.summary()